In an effort to improve search results provided to users, many search engines have begun to incorporate geographic data in identifying search results. For example, a user searching for “restaurants” may be provided with relevant search results as to restaurants generally, but also influenced by the user's current location and restaurants nearby. Thus, the user may be presented with results to nearby restaurants, as well as results regarding restaurants as identified using the search engine's normal searching algorithms.
In many instances, search engines use distance when identifying information to be included in, or filtered from, search results. For instance, when searching for a restaurant, the search engine may identify and include restaurants that are closest to the user in terms of distance, such as based on driving time and/or mileage. However, in some cases, the distance of a user to a merchant location may be misleading to both the user and the merchant. For example, the user may be geographically close to a merchant, but due to the layout of roads and/or levels of traffic, the merchant may be far away from the user in terms of the time it would actually take the user to get to the merchant.
Furthermore, in some instances the merchant's usual customer base may be located in a different location from the user, or a merchant who is preferred by people in the user's location may be located further away from the user than other merchants and thus left out of search results, or, in some cases, may be excluded by the search engine algorithm. Thus, there is a need for a technical solution to providing search engine results that are filtered based on the trade area of merchants.